Systems for Automatic Driverless Movement for Self-Parking Processing

ABSTRACT

A method for navigating a vehicle automatically from a current location to a destination location without a human operator is disclosed. The method includes identifying a vehicle location using global positioning system (GPS) data regarding the vehicle. Also included is identifying that the vehicle location is near or at a parking location. Then, using mapping data defined for the parking location. The mapping data at least in part is used to find a path at the parking location to avoid a collision of the vehicle with at least one physical structure when the vehicle is automatically moved at the parking location. The method includes instructing the electronics of the vehicle to proceed with controlling the vehicle to automatically move from the current location to the destination location at the parking location. The electronics use as input at least part of the mapping data and sensor data collected from around the vehicle by at least two vehicle sensors. The path is configured to be updatable dynamically based on changes in the destination location or changes along the path. The destination location is a parking spot for the vehicle at the parking location.

CLAIM OF PRIORITY

The present application is a continuation of and claims priority to U.S.application Ser. No. 13/934,215, entitled “METHODS AND SYSTEMS FORCLOUD-BASED DATA EXCHANGES FOR REMOTE VEHICLE CONTROL AND DATA SHARING,COMMUNICATION FOR AUTOMATIC DRIVERLESS MOVEMENT, ACCIDENT AVOIDANCECONTROL AND NOTIFICATIONS”, filed on Jul. 2, 2013, which claims priorityto U.S. Provisional Patent Application No. 61/757,020, filed on Jan. 25,2013, and entitled “METHODS AND SYSTEMS FOR CLOUD-BASED DATA EXCHANGESFOR REMOTE VEHICLE CONTROL AND DATA SHARING, COMMUNICATION FOR AUTOMATICDRIVERLESS MOVEMENT, ACCIDENT AVOIDANCE CONTROL AND NOTIFICATIONS”, allof which are herein incorporated by reference.

U.S. application Ser. No. 13/934,215 also claimed priority from U.S.Provisional Patent Application No. 61/760,003, filed on Feb. 1, 2013,and entitled “METHODS AND SYSTEMS FOR VEHICLE SECURITY AND REMOTE ACCESSAND SAFETY CONTROL INTERFACES AND NOTIFICATIONS”, which is hereinincorporated by reference.

U.S. application Ser. No. 13/934,215 also claimed priority from U.S.Provisional Patent Application No. 61/745,729, filed on Dec. 24, 2012,and entitled “METHODS AND SYSTEMS FOR ELECTRIC VEHICLE (EV) CHARGING,CHARGING SYSTEMS, INTERNET APPLICATIONS AND USER NOTIFICATIONS”, whichare all herein incorporated by reference.

U.S. application Ser. No. 13/934,215 also claimed priority as acontinuation-in-part of U.S. application Ser. No. 13/452,882, filed Apr.22, 2012, and entitled “ELECTRIC VEHICLE (EV) RANGE EXTENDING CHARGESYSTEMS, DISTRIBUTED NETWORKS OF CHARGE KIOSKS, AND CHARGE LOCATINGMOBILE APPS”, which claimed priority to U.S. Provisional Application No.61/478,436, filed on Apr. 22, 2011.

All above identified applications are incorporated herein by reference.

FIELD OF THE EMBODIMENTS

The present invention relates to systems and methods that enablevehicle-to-vehicle communication for accident avoidance.

BACKGROUND

Vehicles, such as motorized vehicles and electric vehicles have beenaround for some time. Vehicles provide a means that enable humans todrive from place to place. In today's world, vehicles have become anindispensable mode of transportation, and provide the freedom to travelat any time of day and for various distances. Vehicles can be publicallyoperated or can be privately owned. Humans most commonly operatevehicles, no matter the type, whether electric or combustion enginebased.

In recent years, technology has been advancing, yet accidents occur fartoo often. There is a need for ways to implement technology to assistdrivers to avoid or reduce accidents.

It is in this context that embodiments of the invention arise.

SUMMARY

Methods, computer systems, and servers for processing collisionavoidance feedback to vehicles using vehicle-to-vehicle wirelesscommunication, are provided.

In one embodiment, a method for navigating a vehicle automatically froma current location to a destination location without a human operator isprovided. The method includes identifying a vehicle location usingglobal positioning system (GPS) data regarding the vehicle. Alsoincluded is identifying that the vehicle location is near or at aparking location. Then, using mapping data defined for the parkinglocation. The mapping data at least in part is used to find a path atthe parking location to avoid a collision of the vehicle with at leastone physical structure when the vehicle is automatically moved at theparking location. The method includes instructing the electronics of thevehicle to proceed with controlling the vehicle to automatically movefrom the current location to the destination location at the parkinglocation. The electronics use as input at least part of the mapping dataand sensor data collected from around the vehicle by at least twovehicle sensors. The path is configured to be updatable dynamicallybased on changes in the destination location or changes along the path.The destination location is a parking spot for the vehicle at theparking location.

In one embodiment, a method for navigating a vehicle automatically froma current location to a destination location with or without a humanoperator is provided. The method includes receiving a vehicle location,determining if the vehicle location is near a self-park location, anddetermining if the vehicle is proximate the self-park location for athreshold period of time that is indicative of the vehicle desiring toenter the self-park location. The method includes accessing mapping datafor the self-park location and receiving a request to initiate aself-park process for the vehicle. The method also includes instructingthe vehicle to proceed with the self-park process. The self-park processacting to enable the vehicle to automatically move from a currentlocation to a destination location within the self-park location. Thecurrent location and the destination location are updated dynamically asthe current location of the vehicle changes and based on conditions ofthe destination location.

In some embodiment, the self-parking location includes a plurality ofsensors, each of the sensors being associated to physical locations inthe self-parking location, and selected ones of the sensors monitoring avolume of space to detect changes.

In some embodiment, the changes in the volume space include presence orlack of presence of objects over time.

In some embodiment, the objects present in the volume space include oneof humans, pets, vehicles, or objects determined to be other than freespace for the vehicle to move, park or traverse.

In some embodiment, the sensors of the self-parking location includesensors of one or more vehicles located in the self-parking location.

In some embodiment, the self-park location is one of a parking garage, aparking lot, a private property area, a garage and drive-way, a privateresistance, a public location, or a combination of private and publicspaces.

In some embodiment, instructing the vehicle to proceed with theself-park process is initiated via a remote computing device, and theremote computing device is a computing device that is either portable ornot portable and the computing device has access to the Internet tocommunicate with cloud services, the cloud services including an accountfor users to register their vehicles and access historical data and setcontrol data for the registered vehicles.

In another embodiment, a method includes detecting proximity separationbetween a first vehicle and a second vehicle. At least one of thesensors of the first vehicle or the second vehicle used to determinethat a proximity separation is less than a threshold distance. A pairingalgorithm is triggered between electronics of the first and secondvehicle to enable direct communication for data exchange between thefirst and second vehicles. The method includes triggering a warning toone or both of the first and second vehicles if the data exchangedetermines that a probability exists that a heading of the first orsecond vehicles will result in a collision between the first and secondvehicles. The method may initiate corrective action by one or both ofthe first or second vehicles if the data exchange between the first andsecond vehicles increase the probability that the heading will result ina collision between the first and second vehicles.

In some embodiments, the second vehicle is either moving or stationary.

In some embodiments, the wireless communication includes automaticallypairing for communication between the first and second vehicles, thepairing being for a temporary period of time while the first vehicle iswithin the separation distance of the second vehicle.

In some embodiments, the wireless communication includes short formcommunication, or peer-to-peer communication, or Wi-Fi communication, orNFC communication, or Bluetooth communication.

In some embodiments, further included is detecting additional vehicleswithin the proximity separation of the first vehicle, and tracking thespeed and heading of the additional vehicles relative to the firstvehicle to determine if the warning or corrective action is to beexecuted.

In some embodiments, the exchange of data occurs during a period of timewhen the second vehicle or any one of the additional vehicles are withinthe proximity separation.

In some embodiments, further included is detecting that the secondvehicle is within a proximity separation of the first vehicle usessensor data, the sensor data obtained from the sensors of either thefirst and second vehicles, the sensors include global positioningsensors, or audio sensors, or camera sensors, or ultrasonic sensors, orinfrared (IR) sensors, or combinations of two or more thereof.

In some embodiments, the electronics of each of the first and secondvehicles include a network interface to enable the wirelesscommunication, wherein at least one of the network interfacescommunicate with a process executed by respective electronics, theprocess is configured to manage a table that stores metrics of the firstor second vehicles, the metrics include at least speed and heading ofvehicles within the proximity distance, the table is configured to beupdated over time based on which vehicles are within the proximityseparation.

In one embodiment, a method for providing collision avoidance feedbackto vehicles is provided. Electronics are incorporated in a first vehiclethat receives input from at least one sensor of the first vehicle andelectronics that are incorporated in a second vehicle receive input fromat least one sensor of the second vehicle. The method includes detectingproximity separation between the first and second vehicle, wherein whenat least one of the sensors of the first vehicle or the second vehicledetermine that the proximity separation is less than a thresholddistance, a pairing algorithm is triggered between the electronics ofthe first and second vehicle to enable direct communication for dataexchange between the first and second vehicles. The method also includestriggering a warning to one or both of the first and second vehicles ifthe data exchange determines that a probability exists that a currentheading of the first or second vehicles will result in a collisionbetween the first and second vehicles. The method then initiates acorrective action by one or both of the first or second vehicles if thedata exchange between the first and second vehicles increase theprobability that the current heading will result in a collision betweenthe first and second vehicles.

In some embodiments, the warning is supplied to either the first orsecond vehicles in an output form to alert a human occupant in thevehicles.

In some embodiments, the warning includes one of a sound warning, anaudio spoken sound, tactile feedback to a component of the vehicle,light signals within the vehicle, or a combination of one or morethereof.

In some embodiments, the corrective action includes application ofbrakes, application of auto-turning a steering while, a switch toauto-drive mode, acceleration, acceleration and deceleration, orcombinations of one or more thereof.

In some embodiments, detecting proximity separation includes detectingmoving objects, the moving objects include the first and second vehiclesor the vehicles and a non-vehicle physical object.

In some embodiments, the pairing algorithm enables short formcommunication, the communication includes a peer-to-peer communication,Wi-Fi communication, NFC communication, or Bluetooth communication, orwireless communication.

Some embodiments further include storing a history event log ofoccurrences and actions taken when triggering a warning or takingcorrective action, the history event log being communicated over theInternet to cloud processing systems for remote storage and remoteaccess.

Some embodiments further include, triggering recording of audio andvideo surrounding the first or second vehicle when it is determined thatthe probability exists that the current heading of the first or secondvehicles will result in the collision; and transmitting the recordingover the Internet to cloud processing systems for remote storage andremote access.

In some embodiments, a notification regarding the recording is forwardedto one or more predetermined recipients, to an account of a user, to anaccount of a rental car company, to an account of a service provider,wherein the notification is one of an email, a text message, a socialnetwork message, a phone call, an audio alert, an audio/visual alert.

In some embodiments, the notification includes a clip of the recordingor access to the recording on the remote storage via access to anaccount user name and password.

In some embodiments, the notification is sent to an insurance broker ifit's determined that a collision actually occurred, or enables userpermissions for sending to the insurance broker or third party.

In some embodiments, the notification for when a collision actuallyoccurs includes data regarding a heading, or speed, or weatherconditions, or video clips, or license plate images, or personidentification data, or combinations thereof.

DRAWINGS

FIGS. 1 and 2 show examples of a garage where automated parking canoccur or a vehicle and communications with cloud processing, inaccordance with some embodiments.

FIGS. 3 and 4 show examples of a vehicle moving to a parking locationand associated mapping data for the location, in accordance with someembodiments.

FIG. 5 illustrates a vehicle moving from a current location to adestination location, in accordance with some embodiments.

FIG. 6 illustrates exchanges of data for a location and cloud processingservices, in accordance with some embodiments.

FIG. 7 illustrates an example of vehicles moving in proximity to parkinglocations, in accordance with some embodiments.

FIG. 8 illustrates data and processing that may be executed or stored incloud processing, in accordance with some embodiments.

FIG. 9 illustrates a vehicle communication with cloud processing and auser also communicating with cloud processing via a portable device, inaccordance with some embodiments.

FIG. 10 illustrates cloud processing providing parking location data,locator data for parking spots, locators near specific locations, andthe like, in accordance with some embodiments.

FIGS. 11 and 12 show vehicles in range of various parking locations, inaccordance with some embodiments.

FIG. 13 shows example data regarding parking locations and vehicle data,and processing therefor, in accordance with some embodiments.

FIGS. 14-16C illustrate examples of communication between cloudprocessing, locations and vehicles, in accordance with some embodiments.

FIG. 17 illustrates a reservation system, logic for processing andnetworked services, in accordance with some embodiments.

FIG. 18 shows a collection of vehicles all having independent headings,speed and location. Each of the vehicles shown has the ability to becomeaware of all of the other vehicles within a range.

FIG. 19 shows one vehicle, Car 1, communicating wirelessly with othercars around the position of Car1, in one embodiment.

FIG. 20 shows an instance of an asynchronous network in which allvehicles within a certain communication range can “talk” to each otherusing the same protocol.

FIG. 21 shows an example system with interfaces, data storagestructures, sensor inputs, algorithms and vehicle control systems usedin collision avoidance on board each vehicle, in accordance with oneembodiment.

FIG. 22 illustrates one example of metrics data that can be obtained bya transportation vehicle (TV), and communication to and from othernetworked TVs, in accordance with one embodiment of the presentinvention.

DETAILED EMBODIMENTS

Disclosed are embodiments that enable vehicle-to-vehicle communicationfor enabling avoidance of accidents and/or for triggering warnings toavoid accidents.

A number of embodiments are described below, with reference to specificimplementations that refer to vehicles, but such implementations shouldbe broadly construed to include any type of vehicle, structure orobject. Without limitation, vehicles can include any type of movingobject that can be steered, and can include vehicles that are for humanoccupancy or not. Vehicles can include those that are privately owned,owned by corporations, commercially operated vehicles, such as buses,automobiles, trucks, cars, buses, trains, trolleys, etc. Examplevehicles can include those that are combustion engine based, electricengine (EV) based, hybrids, or other types of energy source vehicles. Insome embodiment, vehicles can be fully driverless or the vehicle canoperation partially driverless. The term driverless should be understoodto include cases where a driver is in the driver's seat, yet, someaction by the car is taken place without the person's direct control. Inother cases, the vehicle can be unoccupied, and if the vehicle is madeto move automatically, this can also qualify as a driverless action,function, operation or action.

In one embodiment, a method includes detecting proximity separationbetween a first vehicle and a second vehicle. At least one of thesensors of the first vehicle or the second vehicle determine that aproximity separation is less than a threshold distance. A pairingalgorithm is triggered between electronics of the first and secondvehicle to enable direct communication for data exchange between thefirst and second vehicles. The method includes triggering a warning toone or both of the first and second vehicles if the data exchangedetermines that a probability exists that a heading of the first orsecond vehicles will result in a collision between the first and secondvehicles. The method may initiate corrective action by one or both ofthe first or second vehicles if the data exchange between the first andsecond vehicles increase the probability that the heading will result ina collision between the first and second vehicles.

In another one embodiment, structures described herein can includeparking structures, parking lots, private or commercial buildings, adrive-through, bridges, toll roads, highways, shared or home driveways,designated driving and parking areas. In the specific embodimentsdescribed herein, vehicles, structures and objects will includecircuitry and communication logic to enable communication with a cloudprocessing system over the Internet. A cloud processing system, asdescribed herein, will include systems that are operated and connectedto the Internet or to each other using local networking communicationprotocols.

A cloud processing system can be defined as an interconnected anddistributed physical or virtual software defined network that utilizesvirtual or physical processing and storage machines that enable variousapplications and operating systems to facilitate the communication withand between various client devices (vehicles, user devices, structures,objects etc.). The communication with and between the various clientdevices will enable the cloud processing system to deliver additionalprocessing information, data, and real-time metrics concerning dataobtained from other processing systems as well as client feedback data.The distributed nature of the cloud processing system will enable usersof various vehicles, structures and objects to access the Internet, andbe presented with more flexible processing power that will provide therequested services in a more effective manner.

The processing systems can be defined from various data centers thatinclude multiple computing systems that provide the processing power toexecute one or more computer readable programs. The processing of thecomputer readable programs can produce operations that can respond torequests made by other processing systems that may be local to avehicle's electronic system. For example, a vehicle can includeelectronics that utilize memory and a processor to execute programinstructions to provide services.

In one embodiment, the services provided by the electronic systems of avehicle can include services that access the various components orsubsystems of a vehicle, such as door locks, service histories, userprofiles, audio settings, entertainment settings, mapping functions,communications systems, telecommunication synchronization systems,speakers, heating and cooling functions, auto-engine start/shut-offremotely via smart devices, remote heating/cooling initiation, remoteface-to-face conferencing, etc. The electronic systems within a vehiclecan also provide a user interface, such as a graphical user interface.The graphical user interface can include a plurality of buttons,controls and transceivers to receive input from a user. The input from auser can also be provided by voice input, facial recognition, eye-retinascan, finger print, or via a touchscreen contained or displayed withinthe vehicle.

In other embodiments, the electronics of a vehicle can synchronize witha user's portable electronics. The user's electronics can include, forexample mobile devices that include smart phones, tablet computers,laptop computers, general-purpose computers, special purpose computers,gaming consoles, etc. The various computing devices of the vehicle, andor the computing devices of the user (smart devices) can be connected tothe Internet or to each other. Provided that a user has access oraccount access to the cloud service, the cloud processing services onthe Internet can provide additional processing information to theelectronics of the vehicle. In the following embodiments, examples willbe provided for ways of having the cloud processing services deliverprocessing information concerning various physical locations that havemapping data associated there with. The following embodiments will alsoprovide examples of ways a cloud processing service, together withphysical sensors, can allow vehicles, structures and objects to becomeaware of each other, share locations, measurements and mapping data,intended paths and other metrics along with remote administration of thesame.

The mapping data associated with the various locations can includelocations of objects in the real world. The objects in the real worldcan include roads, sidewalks, buildings, barriers, fencing, parkingstructures, walls or obstacles within a location, doors, positioning ofwalls, location information of other vehicles within a location, sensordata associated with various locations, mapping data that outlines thegeometries of a building or vehicle, sensor location that is staticand/or dynamic, area and volume information within buildings, structuresor areas, sensors for detecting movement or presence of obstacles withina location, data identifying occupancy a specific locations such asparking structure parking spaces, etc. In one embodiment, vehicles canbe fully driverless or the vehicle can operation partially driverless.For instance, a partially driverless car is one that may still have adriver or occupant in a position to control/navigate the vehicle (e.g.,in the driver's seat), but some movement or control will be carried outby the automation of the vehicle. In an example of a parking operation,the driver may remain in the vehicle during some or part of thedriverless actions of the vehicle, and the driver can (if needed)interrupt (e.g., override) the actions automated actions of the vehicle.It should therefore be understood that any mention of driverlessvehicles or actions can, in some embodiments, still include a personwithin the vehicle (whether in full or partial control of the vehicle).

In one embodiment, the sensors of the building, showing the outline ofthe building can provide data of what spaces are available within adesignated parking area for example. When a vehicle reaches a building,parking lot, parking designated area of ad-hoc parking lot whereauto-park is available, the vehicle will become aware of theavailability of non-human operated auto parking and will transfer andreceive information to and from the cloud to download and/or access thebuilding's location and map of sensors. When a vehicle reaches adifferent auto-park location, it will download that particular map. Themap will only be downloaded or accessed when it is determined that thevehicle desires to enter the parking structure either by crossing aproximity threshold of by election of the vehicle's operator. Thus, athreshold of time or proximity can be determined before the car gets themapping information for the given location. For example, if a vehicle isparked near the entrance of a parking structure (determinedautomatically by the GPS of a vehicle and the GPS of parking structure),this proximity produces a type of optional “paring” with the garagelocation which a vehicle operator can elect to enter using a physical orremote cloud connected interface to select an outcome.

In one embodiment, vehicles can maintain valuable information regardingwhere they are, where they are heading and their destination maintainedwhich is maintained by GPS and navigation systems on board. Theinformation collected and maintained by every vehicle is mutuallyexclusive, meaning that only each individual vehicle is aware of its ownheading, rate of speed and current location. This information, on oneembodiment is crowd sourced and crowd shared/consumed for use in foraccident avoidance. By networking vehicles within a certain radiustogether, all individually location-aware vehicles become also aware ofall other vehicles in their sphere of influence. Every vehicle willnetwork with vehicles in their range using wireless communicationsystems such as but not limited to Wi-Fi, Wi-Gig LTE, cellular, radio,near field communication or other methods.

In one embodiment, each vehicle will maintain a table of all othervehicles in, entering, and or leaving its sphere of influence. In someembodiments, all or some of the vehicle will maintain and continuouslyshare its own heading, speed and location. In one embodiment, analgorithm on each vehicle will continuously compare the currentvehicle's speed, heading and location with that of all other vehicles inits sphere of influence to determine if a collision may result.

A vehicle collision is not a single event; it is the intersection thathappens between two vehicles having intended paths, headings, and speedsthat perfectly collide at some point in the future if course correctionis not taken. Thus, an algorithm may be able to predict the probabilityof a future collision where a human may not, and alert the driver toalter heading and/or speed. The system will have the ability to enactpassive and active accident avoidance vehicle maneuvers in proactiveaction to an imminent collision.

The system may alert the drivers to change their rate of speed, heading,or location. The system may give each of the two driver's custommessages such as telling both drivers to veer right so they don't steerinto each other. The vehicle may also automatically provide audio and orvisual alerts such as honking the horn or flashing headlights to alertthe other driver. Active accident avoidance may engage if certaincollision is immanent within a certain threshold such as within the next50 ft for example. In this case, both vehicles, being aware of eachother, will engage in an automatic and complementary accident avoidancemaneuver such as slowing down, steering away from impact and or both.The vehicle may engage secondary methods of identifying imminentcollision such as radar, sonar, infrared or other secondary objectidentification method to ensure the predicted collision is not a falsealarm.

The vehicle's cameras can be engaged to take still photos and or videorecord any incident, whether it results in a successful avoidance orimpact. This footage can be used to alert authorities of the severity ofthe accident and aid insurance companies in identifying fault. A vehiclewill maintain a buffer of events for a given amount of time before andafter a collision event or collision avoidance event such as thelocation, speed, heading, and avoidance measures to store and identifythe metrics that lead to an incident.

This system described above can be used not only between two vehiclesfor the purpose of accident or collision avoidance, but can also be usedbetween a vehicle and an object, a vehicle and a moving object, avehicle and a structure as well as a combination of vehicles, objectsand structures. The methods for accident avoidance between two vehiclescan be extended for use in automated vehicle maneuvering. Thismaneuvering includes but is not limited to negotiating obstacles,structures, parking lots, drive ways, toll roads, highways, drive-thru,etc. These obstacles, can be physical or virtual where a vehicle mightinterpret a virtual boundary of an object or parking spot for instanceas being real and thus having to maneuver in, on or around it for thepurposes of collision avoidance, parking or automated vehicle storage.

Vehicle storage can be automated at physical static locations or can bedeployed manually in an ad-hoc manner with the use of portable sensorsthat emit a signal to network connected devices, vehicles, objects andstructures transmitting metrics and dimensions the sensor isvirtualizing at that given moment. For instance, a sensor can be set upto communicate with a vehicle that it represents a parking spot. Thisparking spot can transmit information about it such as what type or spotit is, its dimensions, its availability, if it has a charging stationincorporated into it, scheduling, availability as well as on the flybooking of the spot for parking time, charging time etc. either remotelyor within a proximity threshold by a user in or around their vehicle orremotely.

FIG. 1 illustrates an example of a location, such as garage 100 having aplurality of sensors S1 through S12. The sensors are located in variouslocations within the garage 100. The sensors provide mapping informationof the physical structures within the garage 100. This mappinginformation provided by the garage 100 (or cloud system database of thegarage 100) can be transmitted to vehicles that will then be allowed totraverse the garage 100. The vehicle will also now be informed of thespecific locations of the objects within the garage 100 or of the garage100 itself to dynamically and actively avoid collision with thestructure's physical obstructions. As shown, the garage 100 will also bein communication with a global positioning system (GPS) 102, whichassigns garage 100 GPS a location as well as a set of locations whichcan be used in mapping outlines of the structure. The GPS locations canbe assigned to the garage 100, or to various locations within thegarage. For example, GPS coordinates can be assigned to each of thesensors S1-S12 of garage 100 or to the entire structure itself. In oneembodiment, the GPS coordinates of each of the sensors may beapproximated, due to a potential offset of the sensor's actual GPScoordinates due to interference, weather, malfunction etc. This offsetcan be calibrated for each of the sensors, such that the actual locationof the sensors can be associated or dynamically corrected for the GPScoordinates assigned to each of the sensors.

In one embodiment every time a vehicle receives coordinates to thelocation of a certain sensor, the vehicle will travers towards thatsensor and verify through the use of ad-hoc networking, sonar, infrared,radar or other method that the location given to the vehicle of thesensor matches its physical location. If the actual physical location ofthe sensor does not match the coordinates furnished to the vehicle, thevehicle will report back to the cloud processing system in order tocorrect the coordinates for transmission to the next auto-traversingvehicle. This will provide a vehicles traversing within garage 100 withmore accurate identification and location of obstacles within garage100. Without correcting the GPS coordinates, it is possible that avehicle will come into in appropriate contact with an object withingarage 100. In other embodiments, each of the sensors S1-S12 will becalibrated to a GPS location, and the calibration can also be assignedto the GPS location of the vehicle traversing within or here orapproaching garage 100.

In the example shown, a vehicle v1 is shown entering garage 100, andanother vehicle v2 is shown driving along a path to a desired orassigned parking location. As shown, other vehicles v3-v4 may already belocated within garage 100. In one embodiment, each of the vehicles willalso have sensors that will alert the cloud processing of their locationwhen another vehicle or object approaches that particular vehicle. Thus,the movement of vehicle v2 and the location of vehicles v3-v5 will beknown to the cloud processing system and all vehicles (or those enabledfor communication) within the given range will also be aware of eachother. As such, the system uses a combination of sensors located ingarage 100 as well as sensors located on vehicles themselves to aidvehicles in traversing the garage 100 or maneuvering around obstacles aswell as vehicles already stationed or moving about garage 100. In oneembodiment, each of the vehicles within garage 100, whether the vehicleis turned on or turned off, will still be able to provide location andor sensor data to the cloud processing system 120. Sensors within garage100 can also include information concerning the volume or areas ofindividual parking designated physical or virtual spots within garage100. This additional sensor data can be transferred to a sensor dataprocessor 104 of garage 100. Sensor data processor 104 can communicatethat information to cloud processing 120 via a wireless router 106, orother suitable wired or wireless communication system that allowsconnection between garage 100 and the Internet.

As shown, vehicle location data 108 of each of the vehicles, structuresor objects that are proximate the garage 100 can communicate theirlocation data to cloud processing 120 so that information concerning thegarage 100. Sensors that are fixed as well as sensors within garage 100can locate- or identify moving objects which can be communicated to thecloud processing system along with data of the vehicle location data108. Vehicle control data 110 can also be provided to cloud processing120. Vehicle control data can include information that is provided to aspecific vehicle to directing that vehicle to park. For example, ifgarage 100 enables automatic vehicle parking, such as parking operationsthat do not involve the human to drive the vehicle, that vehicle can beprovided with vehicle control data 110. Vehicle control data 110 can beprovided via cloud processing 120 to any specific vehicle.

Information provided to a specific vehicle can include, for example, anoperator of the garage 100 enabling a user to select or identify adesired parking location for the vehicle in garage 100. In oneembodiment, a user may approach garage 100 and desires to park his orher vehicle in garage 100. At the entrance of garage 100, the user canidentify a parking space for the vehicle and then exit the vehicle. Thevehicle is then automatically moved to the desired or specific parkingspot identified either by the vehicle's user or by a garage 100operator. In one embodiment, the a vehicle user approaches the garage100 while operating the vehicle. When the vehicle's GPS detects that thevehicle may be in proximity to garage 100, mapping data associated withgarage 100 is downloaded or made accessible to the vehicle'selectronics. The vehicle's electronics will become aware of the mappingdata for garage 100. The vehicle's user may then choose to program thevehicle to automatically park using a graphical user display in thevehicle. Similarly, the user may elect to program the vehicle toautomatically park using a smart network connected device (smart phone,tablet, computer, etc.). Once programed by the vehicle user, the vehiclecan proceed to automatically move to the desired parking spot or aparking spot that the garage 100 designates for that vehicle.

For example, the user may wish to have the car parked in a VIP area ofgarage 100. If the vehicle's owner selects the VIP area, or is grantedaccess to VIP areas, the vehicle may be parked in a more convenientlocation within garage 100. The parking slots in garage 100 can bemonitored with sensors to identify which parking spots are available.When the user provides a parking location preference election at theentrance of garage 100, the vehicle will proceed to park in garage 100at the desired location automatically. In one embodiment, garage 100 mayhave a plurality of floors or levels. The vehicle can now traverseautomatically to a specific floor and find the parking spot at which thevehicle will be stationed.

Since a multi-floor or multi-level parking garage has a height, simpleLAT, LONG GPS coordinates alone cannot aid the vehicle in traversingvertically to the desired floor. Thus, the aid of additional sensors inconjunction with GPS can aid the vehicle in negotiating the parkinggarage's obstructions, levels, and parking slot locations. Thisinformation can be obtained by rules or databases provided by garage 100to the vehicle, and the direction or vehicle control data 110 can beprovided by the user of the vehicle who desires to have the vehicleparked in garage 100.

FIG. 2 illustrates an example of data and data sources that cancommunicate with a cloud processing 120. Example data can includevehicle position data 162 which can include data of moving objectsrelative to local sensors. For example, the data can include how fastthe vehicle is moving 150 when the vehicle moves past specific sensorslocated within garage 100. Local sensor data 152 of the vehicle can alsobe used to provide vehicle position 162. Local sensor data 152 can alsoinclude sensor data from other vehicles that may be stationed withingarage 100. This local sensor data can also include sensor data of othervehicles that may be moving within garage 100, for example, the heading,speed, and other coordinates of vehicles that may be moving in proximityto other vehicles.

By using this information, it is possible to define rules that avoidvehicle collisions when a plurality of vehicles are in proximatethresholds of one another in garages or locations that allowself-parking or self-moving of vehicles without human drivers. GPS data154 can also become indicated to identify vehicle position 162, asdescribed above. GPS data can be location GPS data from one or more GPSsatellites. The GPS data can also be obtained for moving objects orstructures 160. Vehicle movement directions 164 can also be identifiedor communicated between the vehicle position 162 data based on humanoperated vehicles 166, and automatic remote driving 168 vehicles. Cloudprocessing 120 will also provide easy communication for user 180. User180 can be using a mobile device 103 to communicate with cloudprocessing 120. For example, an application on a mobile device 103 cancommunicate with cloud processing 120, which in turn will enable theuser to select that the vehicle perform self-parking operations, can payfor parking privileges, can be provided with notifications of thelocation of the vehicle that has been parked in garage 100, and can beprovided notifications or information when the vehicle is moved withingarage 100. User 180 can also access cloud processing 120 from anycomputer connected to the Internet, which will allow the user to viewstatus reports regarding the user's vehicle, including when the vehicleis automatically driving itself, its current position, a history of itslocations at any given time, its status when located within the parkingstructure or location, etc.

FIG. 3 illustrates an example of location A 250, in accordance with oneembodiment of the present invention. In this example, a partial view ofa parking structure is shown, where a plurality of zones within theparking structure are identified. The zones are identified as zones a-I.The zones can be identified in terms of their volume, or 2 dimensionalspace. The sensors can include audio sensors, visual sensors such ascameras, ultrasonic sensors, IR sensors, etc. Any of these sensors canprovide details regarding whether the location includes an object,identifies the object, identifies a moving object, identifies an objectthat should be in that location, identifies an object that should not bethat location, logs information regarding objects in specific locations,etc. In this example, a vehicle v3 is moving from a current location toa destination location. The destination location is a parking space inzone C.

Various sensors S1, S2, S3, S4, S5, are located throughout location A.Specific locations shown for the sensors is not important, as thesensors can be located in any location, whether to identify volumes ofspace, weight of vehicles, presence of vehicles, presence of humans,presence of pets, presence of other vehicles, presence of other vehiclesmoving, relative movement of vehicles or objects, etc. As the vehiclemoves and traverses a path, a human 200 is shown to be located in zonef.

This information is provided to cloud processing 120 and suchinformation can assist in stopping the vehicle from colliding with human200. In one embodiment, cloud processing 120 may communicate with one orall of the fixed sensors of location A, some of the fixed sensors, dataproduced by the sensors, data produced by other vehicles within thelocation, information generated by the moving vehicle that is traversingbetween the current location and destination location, etc. Thisinformation is being communicated and exchanged with cloud processing120, as each vehicle will include processing power as noted above tocommunicate over the Internet concerning its location, its movement, itsrelative movement other vehicles, and a programmed path which thevehicle is to traverse.

FIG. 4 illustrates an example of information 202 that includes mappingdata 210 for location A, in accordance with one example of the presentinvention. In this example, mapping data 210 can include, withoutlimitation various information metrics, including building outline,sensor locations, coordinates of sensors, GPS data for sensors, GPS datafor location A, correction data for calibrated GPS locations of sensors,etc. In addition, the very sensor locations can include fixedstructures, such as structures X and Y. These structures would be staticstructures within the location. The sensor locations can also identifyfollowing areas, such as volume areas a-I. As mentioned above, thevolume areas can produce dynamic data, as information regarding what ispresent in those specific volume areas changes over time, includingchanges occurring while vehicles are in progress in their move between acurrent location and destination location.

These dynamic changes are in important to continuously monitor andupdate back to cloud processing 120, so that cloud processing 120 cancommunicate updates to the vehicle in substantial real-time. Also shownare sensor location alerts. Alerts can include alerts to the operator ofa specific location (for example the parking garage attendant), theowner the vehicle, or another process that automatically terminatesmovement of the vehicle when an obstacle is presented. Various rules anddatabases can be accessed to determine what actions vehicles can take orshould take when specific obstacles are encountered, and when thevehicle can resume movement after encountering such an obstacle.Tracking when the obstacles are encountered and where they areencountered can also be utilized to define metrics for specificlocations. For example, if certain locations produce a lot of alerts,that location needs to improve its management of space to avoidaccidents.

The tracking can also be used to generate reports/notifications that areproduced and distributed to safety coordinating officers of specificlocations (or vehicle owners), or to identify information that occurredbefore or after an accident or incident at a specific location such as avehicle collision, vehicle theft of attempted theft, robbery, attemptedrobbery as well as panic situations during crimes. These alerts can alsobe provided with historical data associated with the alerts. Thehistorical data can include images taken by cameras of the specificlocations where the alerts occurred. The images can be videos, videoclips, still images, collection of still images, audio files, audiosnippets, that are accessible instantly over cloud processing 120.

This information can also be accessible via cloud processing 120 after aspecific incident is reported. For example, if a burglary or crimeoccurred within the location, the sensor data of the location as well asthe sensor data of the vehicles can be coordinated to identify when andwho traversed specific locations within the area. In one embodiment, thecollected data can be partitioned to allow certain data to be sharedwith the owner of the vehicle and certain data to be restricted to theowner or operator of the location where the vehicle is self-parked.

FIG. 5 illustrates an example where each of the vehicles parked in thelocation 250 can include sensor data. The sensor data for vehicles v1and v2 are shown as slight outlines around the vehicle. In this example,these vehicles are parked in spaces b and d. As vehicle v3 moves along apath to a destination location, the sensors of the parked vehicles v1and v2 are also utilized by the cloud processing system 120, along withdata from sensors of moving vehicle v3, to avoid collisions withvehicles within location 250. For example, if any of the parked vehicleswere to begin to move, that information can also be used in conjunctionwith the information of the 1st moving vehicle, thus avoiding apotential collision when the vehicles are in self-drive mode.Incidentally, the sensor information is also utilized or be useful toprevent accidents when the vehicles are being used or driven by humans.Accordingly, the sensor information described herein, and ifsynchronization with cloud processing system should not be limited toself-driving vehicles, but can also be applied to any vehicle that isbeing driven to avoid collisions between the vehicles when there isbetween self-driving and self-driving, or human driven and self-driving.

FIG. 6 illustrates an example of the types of data that can be providedand associated with a location A to generate mapping data for thatlocation. In this example, without limitation, various pieces of datacan be communicated or associated to a location. For example, buildingoutline data 302, sensor locations 304, coordinates of sensor locations306, GPS data for sensors 308 and any calibration data, GPS data forlocations 310, sensor data from other vehicles (which may be dynamic asvehicles move or are stationary) 312. This information can be associatedto define the mapping data of a location 210. Cloud processing systems120 can then receive the mapping data 210 to enable execution ofrequests for self-parking. For example, a user using a mobile device caninstruct or request that a vehicle begin a self-parking operation. Forexample, if the user drives up to a parking structure or garage, andthen selects on their mobile device to park the vehicle, the vehiclewill communicate with the cloud processing system and instruct thevehicle on how to proceed to park the vehicle within the parkingstructure by maneuvering and negotiating obstructions.

The cloud processing system can therefore provide parking instructionsto the vehicle (for example vehicle v3) that is to be parked andlocation A 250. The instructions can include how to move the vehiclewithin the parking structure, or simply provide the mapping data of thevehicle to allow electronics within the vehicle to traverse the vehiclewithin the location. In other embodiments, the information as to how tomove the vehicle within a specific structure may be governed by specificrules of the specific structure. For example, specific structures mayrequire the vehicles being told to park can only move at 5 miles anhour. In other embodiments, the cloud processing system can be providedwith a range of speeds that can be dictated to specific vehicles forspecific locations. Therefore, a set of rules is exchanged between thecloud processing system and a specific location.

In one embodiment, when a user decides to park a vehicle in a parkinglocation, that parking location may be a registered parking locationwith cloud processing systems. By being registered, any number ofvehicles that also have access to cloud processing systems and have anaccount can enable users to park using some park algorithms for thespecific parking locations. By being a registered parking location thataccepts self-driving parking vehicles, the registered parking locationcan send rules back to the cloud processing system to dictate where andhow and at what speeds vehicles shall be parked within the location.Duration of parking within the location can also be communicated back tothe cloud processing system as well as the fee charged to the user fortime parked within a parking structure.

A user's account can be debited automatically, such as using ane-commerce debit system once the vehicle has been parked in a specificlocation. Notifications to the user can also be provided when the userhas parked at a specific location, such as time in, time out andduration of park at a specific location as well as any associatedcharges and overtime fees. The user can also be provided with anapplication interface that allows the user to extend the time ofparking, and pay for extended periods of parking within a location orset up automatic parking fee renewals to avoid expired meters forinstance. The user can also provide cloud processing systems with rulesfor how the vehicle shall be moved within the location. For example, theuser may wish that the automatic park system only move the vehicle at 3miles an hour. In this embodiment the user can set the speed at whichthe vehicle can be auto parked. In other embodiments, rules between theparking location, the cloud processing system, and those set by the usercan be synchronized or sorted out to define the appropriate speed,location of parking, and other parameters for moving a vehicle usingself-driving techniques.

FIG. 7 shows an example where a vehicle has entered a proximity zonearound a specific location, and the vehicle has communicated with cloudprocessing 210 as well as the location. In this example, if the vehicleenters the proximity of a specific location, that vehicle will beprovided with mapping data of that location. In one embodiment, themapping data can include the data associated with the location such asthe coordinates of the physical structures, and/or moving objects withina location. However, the mapping data can be simply made accessible tothe vehicle, without downloading.

In either case, the vehicle will not need the mapping data for alllocations at all times, and the mapping data for specific locations willbe made available when the vehicle enters the proximity zone around thelocation. Thus, if the user driving the vehicle is far from a specificlocation, the mapping data for that location will not be made accessibleto that vehicle. In other embodiments, when the vehicle has entered theproximity zone around a location, and that vehicle is in that proximityzone for a threshold period of time, the mapping data will be madeavailable or downloaded to the vehicle. For example, if the vehicle hasentered the proximity location of a location for at least 2 min., thenthe mapping data will be made available to that vehicles electronicssystem. In other embodiments, the threshold period can vary and can beset by the cloud processing system. Examples can include a threshold of10 seconds, 20 seconds, 30 seconds, 1 min., 3 min., 4 min., 10 min.,etc.

FIG. 8 illustrates an example of cloud processing 120, where databasesholding data of location with self-park functions 402 can be monitoredand managed. In one embodiment, the various locations and sets of GPSlocation information can be stored in a database, and that data can beupdated with location data updating 404. Varies examples of data updatesare provided in FIG. 8, and such information can be uploaded to or madeaccessible to the various databases. As noted above, the databases andprocessing can be managed in a distributed processing fashion. Thedistributed processing can be across multiple geographic locations,multiple data centers, multiple virtual machine processing systems, etc.In one embodiment, cloud processing 120 can include logic for vehiclepark request handlers 406, GPS data vehicles requesting self-park 408,vehicle and location proximity detection 410, proximity thresholddetection 412, etc. This information can then be synchronized withmapping data of the various locations and the mapping data can then becommunicated to the various vehicles when the mapping data is needed bythe various vehicles.

FIG. 9 illustrates an example where cloud services 120 forwards mappingdata for location A to a vehicle, and the vehicle electronics 450receives the information. This information will be communicated to thevehicle continuously, at certain times, or on demand. In one embodiment,the vehicle electronics will also include the Internet communicationprotocols and systems to maintain wireless connectivity during movementof the vehicle, or when the vehicle is stationary. In one example, thevehicle electronics can accept mapping data 210, which may be updateddynamically as noted above. The mapping data can be provided to theself-park controller 454 of the vehicle. Vehicle sensors 452 of thevehicle can be communicating data to the self-park controller as well asvehicle cameras. The vehicle cameras can also be obtaining data during,after or before the vehicle begins to move. The vehicle cameras can belocated in all locations around the vehicle. The vehicle cameras can belocated in the front, in the rear, under the vehicle, above the vehicle,to the sides of the vehicles etc. Other sensors the vehicle can includeultrasonic sensors, heat sensors, IR sensors, sound sensors,microphones, etc.

Other examples of sensors, biometric sensors, and systems, may include,for example, those described in co-pending application entitled “Methodsand Systems for Setting and/or Assigning Advisor Accounts to Entitiesfor Specific Vehicle Aspects and Cloud Management of Advisor Accounts”,having application Ser. No. 14/063,837, filed on Oct. 25, 2013, which isherein incorporated by reference.

In one embodiment, this data can be provided to the self-park controller454 and the self-park controller 454 can communicate with the drivecontrol 456. Drive control 456 can then communicate with the vehiclesystems to move the vehicle to a desired location. As the vehicle moves,or the vehicle is stationary, specifications for 60 can be provided tothe cloud server 120, to allow user 180 to view dynamic status updatesconcerning the vehicle at all times. A portable device 103 is shownbeing held by the user 180, but it should be understood that an type ofdevice connected to the Internet and having access to cloud server cancommunicate with the vehicle to provide receive or send notifications orcontrol to the vehicle.

FIG. 10 illustrates an example where various locations 402 providestatus to cloud services system 120. In this example, the variouslocations are registered locations with cloud services, so that anyvehicle can access any location and obtain information concerning thelocation, such as mapping data. In one embodiment, users may wish to getinformation, such as information helpful for finding a parking spotnearby. This information can be communicated by the vehicle electronicsor a portable device of the user 103 to cloud services requesting if thecurrent location has a parking space nearby the GPS coordinates of thevehicle. In another embodiment, a user needs to be in the vehicle tofind open spaces near specific store or commercial location or mappeddestination. In other embodiments, the user may wish to locate a coffeeshop and find a space near the coffee shop. This information can also beobtained from cloud services, as the locations within 402 will holdinformation about what locations parking spots are open at anyparticular point in time.

In one embodiment, advertisers can also sponsor parking spots if usersview an advertisement. In still other embodiments, advertisers can setup rewards for parking a certain locations, and the locations can bebranded for the advertiser for a given period of time. For instance,advertising in a parking location can be digital, in the form of screensplaced near and around the parking location. When a user for which anadvertisement is destined enters the garage or moves around a parkinglocation, the advertisement on the screen can be custom changed for thatperiod of time when the user is near the screen or area of the parkinglocation. Since the user's parking was sponsored by the advertiser, theuser should expect to see advertising from that advertiser in and aroundthe parking location.

FIG. 11 shows in one embodiment, a collection of vehicles, parkinggarages, parking queues, parking lots and ad-hoc parking areas 1100 allhaving independent headings, speed and location if applicable. In oneembodiment, each of the vehicles, structures and objects shown have theability to become aware of each other within a range 1102. Car 1, beingone example, shows a sample radius of awareness around it. In thisexample, Car 1 is aware of Car 2, Car 4, Car 3, parking garage 2, andparking queue 2. Car 1 also keeps track of their heading, speed andlocation at any given time if applicable. Car 1 also knows that Car 2 isleaving Car 1's sphere of influence. Car 1 also knows that it isentering parking garage 2 and parking queue 2's sphere of influence.

Just as Car 1 is aware of all other vehicles, objects and structuresaround it, all other vehicles, objects and structures shown in thisdiagram 1100 may behave in the same manner. For instance, Car 1 is notonly keeping track of all other vehicles, objects and structure in itsvicinity, Car 1 may also be broadcasting its speed, heading and locationinformation so all other cars, objects and structures in this diagram1100 are aware of it as well. This system exists in the presence of aconstantly networked environment where vehicles, objects and structuresmay communicate with each other with or without the use of a centralprocessing system.

In some embodiments, the vehicles may establish peer-to-peer links tofacilitate fast transfer of data. In other embodiments, vehicles maylink to each other using pairing algorithms that allow the vehicles toexchange data using WiFi, Bluetooth, near field communication (NFC), orsome other short range communication protocol.

FIG. 12 shows a system 1200 in which vehicles, parking structures 1204,lots 1202 and virtual ad hoc parking areas 1206 all communicatingwirelessly with all other connected vehicles, structure and objectsaround it with the use of a networked and cloud processing system 120.In this example, Car 1 may be sending its heading, speed and location toall of the other vehicles, structures and objects within communicationrange, GPS coordinate location or network and also receiving every othervehicles, structure and object's heading, speed and location withincommunication range using the same methods.

The use of an asynchronous network in which all vehicles, structures andobjects within a certain communication range can “talk” to each otherusing the same protocol may be employed. In this case, the protocol usedcan be Ethernet through wireless mediums such as 802.11a, b, n, ac, ador any other wireless communication protocol.

FIG. 13 shows a sample system 1300 with interfaces, data storagestructures, sensor inputs, algorithms and vehicle, structure or objectcontrol systems 1302 used in collision avoidance on board each vehicle.Each vehicle will have a network interface, which communicates withother vehicle's network interfaces or a central/distributed cloudprocessing system. Each vehicle will store all data coming in from othervehicles in communication range. In one embodiment, this set of data maybe kept in a table of all or some of the metrics including but notlimited to speeds, headings, locations, outlines, buffers, destinations,driving characteristics and acceleration if applicable. Similarly, eachvehicle may maintain a table of its own metrics including but notlimited to speed, heading, location, outlines, buffers, destination,driving characteristics and acceleration if applicable. This data (orselected data that the user approves for public sharing) may be passedto other vehicles using the network interface, which then communicateswith other network interfaces directly or through an intermediary suchas a cloud processing system, Internet, router, network switch orcombination of methods etc.

The vehicle metrics and data may be collected using a variety of sensorsincluding but not limited to optical sensors, mechanical sensors, andnetworked sensors among others. These sensors can emit data as well ascollect data. For instance, a vehicle may be 5 feet wide by 10 feet longbut in order to communicate its dimensions and outline to other vehiclessensors must be calibrated. These sensors can be calibrated on board thevehicle, remotely through a management system connected to a deviceconnected to the internet or can be transmitted automatically from themanufacturer. The vehicle's dimensions can now be shared with othervehicles on the road in order to avoid collision. The sharing of thisdata can be in the form of shared moving object detection (MOD) data.Thus, not only is one vehicle aware of the MOD around its vicinity, thesame vehicle can be provide data regarding nearby vehicles and their MODdata. Furthermore, buffers can be instituted in order to ensure that thevehicles outline is not breached but extra room is given around eachvehicle to further collision avoidance effectiveness.

Each on board computer on each vehicle may use data coming in from othervehicles together from data captured by the vehicle itself to feed acollision detection and prediction algorithm. In one embodiment, thisalgorithm may activate a collision management system that interacts withthe vehicles control systems including but not limited to audio alerts,visual alerts, horn, headlamps, steering, braking, tactile feedback onthe steering while, tactile feedback on the driver's seat, video andcamera recording, safety restraint systems, combinations thereof, etc.

The collision management system may engage any combination of activeand/or passive collision avoidance maneuvers using the vehicle's controlsystems. For instance, if two vehicles are traveling on intended pathsthat will result in a head-on collision at some point in the future, thesystems on both vehicles will calculate if an early warning willsuffice. Each of the two vehicles will alert their corresponding drivervia audio, tactile feedback near, on or proximate to the driver's body,a visual alert, or combinations thereof. If the drivers do not correcttheir intended path and a collision is still predicted by the algorithm,more aggressive systems will engage such as applying braking power,reducing speed, or steering the one or both vehicles away from eachother or away from an obstacle.

FIG. 14 shows an example of a virtual parking location boundary sensorsystem in conjunction with other virtual parking location boundarysensors and vehicles 1400. A virtual parking location boundary sensor1408 may be deployed in an ad-hoc fashion to provide automatic parkingfacilities in temporary locations or within existing static structures.Once activated, sensor 1408 can transmit data about itself to othersensors, vehicles, structures and/or objects. A sensor 1408 can beinstructed to produce a virtual parking boundary of 10 feet by 15 feetto facilitate the parking of a large vehicle, or the boundary can bedynamically adjustable on demand. The same sensor 1408 can be calibratedremotely using cloud processing 120 to produce a virtual parkingboundary of 10 feet by 40 feet for instance to accommodate a largecommercial semi-truck. Sensor 1408 can be manually laid out in anyfashion as to construct any parking lot as long as the virtualboundaries of each sensor do not overlap. In the event that two sensors1408 are activated and their virtual boundary intersect, a visual andaudio cue will be given to the operator to aid in sensor spacingautomatically. Once the sensors are sufficiently placed where theirvirtual boundaries do not intersect, audio and visual cues will cease.

Sensor 1408 has the ability to communicate with sensor 1404 located onvehicle 1402 for instance for the purposes of guiding a vehicle inparking either manually or automatically self parking at the locationboundary produced by the sensor 1408. Sensor 1408 may communicatedirectly with sensor 1404 or may use cloud processing 120 as anintermediary as well as a combination of the two methods.

FIG. 15 shows one embodiment of a system 1500 where a parking area 1506may exist in conjunction with an automatic parking drop-off location1502. Vehicles that are equipped to use auto parking facilities may useauto park drop off locations such as 1502 to exit their vehicle beforetheir vehicle proceeds to automatically park itself in a given parkinglocation. In this example, a vehicle B has the ability, through the useof it's communication sensor 1404, to communicate with cloud processing120, parking location sensor 1504 and individual parking spot sensors1408 as well as other vehicle's communication sensors (vehicle C in thiscase) in order to safely guide the automatically parking vehicle Bwithout human interaction.

Using communications regarding mapping data, locations and othermetrics, a vehicle can be guided automatically to either the nextavailable virtual parking spot boundary 1512 being produced by a sensor1408 or to a particular virtual parking spot boundary 1512 of thevehicle operator's choosing. This example shows vehicle B beingautomatically guided to a virtual parking spot boundary as it traversesa parking lot, parking garage, ad-hoc parking area, drive way orcharging spot bank area 1506 while dynamically and constantlycommunicating with all structures, vehicles and obstructions around itand with the use of traversing instructions communicated to the vehicle.As vehicle B traverses to its final location within 1505, it dynamicallyand constantly provides feedback to all other dependent sensors andcloud processing systems.

In this example, a portable vehicle charging pad 1514 (or virtual pad)may be deployed and paired with any given sensor 1408 which is deployedto provide a virtual parking spot boundary. Portable vehicle chargingpad 1514 powered by the grid, a generator or solar power 1510 maycommunicate with sensor 1408 through the use of its own sensor 1508 inorder to establish that it is present. 1514 may also communicate with anetworked cloud processing system through the use of its own sensor 1508to aid in dynamic and remote administration (e.g., via GUI screens ofany Internet accessible computing device, whether wired or wireless),reservation and payment options for use as well. After a portablevehicle charging pad pairs with a given sensor 1408, it can beregistered on a remote distributed cloud processing system as ready toprovide charging services. These services may be used on a first comefirst serve basis or through the use of a remote reservation system.

Such combinations or sets of virtual parking spot boundaries 1512emitted by sensors 1408 can be placed in an ad-hoc manner for portal,temporary use such as outside large concert venues, for installation inhome garage or driveway applications as well as large commercial orcivic parking structures and locations. For instance, 10 count 1512parking virtual parking spot boundaries are required for a special eventwhere 5 must also provide charging facilities. A user can deploy 10 1408auto-spacing sensors and pair 5 of them with 5 portable vehicle chargingpads 1514 with the use of 1514's sensor 1508 in communication with 1408.These portable charging pads 1514 may be powered from the grid, agenerator or solar power etc. Once the charging pads are paired with thevirtual parking boundary, they can also be registered with thenetwork/cloud processing 120 to provide in-advance-reservation ability.

FIG. 16A shows one sample of a situation where two vehicles aretraveling in arbitrary manners within a proximity threshold of eachother 1601. Vehicles are registered with a network cloud processing 120at any given time and will register with one another once they are inproximity of each other as well. In this example both vehicles transmitand receive data regarding their speed, heading, dimensions, GPSlocations, trajectories and identification metrics dynamically andconstantly. Vehicles use the transmitting sensors 1404 to communicatewith each other or with cloud processing 120 at any given time. Thisinformation allows vehicles to become aware of not only each other, butalso each other's intended paths, outlines and outlines plus bufferareas so as to maneuver together at the same time automatically withminimal or no human interaction not only in shared roadways but also insmaller contained environments such as parking lots, parking garages,drive throughs, emergency situations and collision prediction andavoidance.

In one embodiment, the vehicles can communicate directly with each othervia a temporary pairing process. The temporary pairing process can beautomatically enabled when vehicles become too close to each other, forexample. When this happens, local communication between the vehicles,such as a peer-to-peer connection, Wi-Fi connection, NFC connection, orBluetooth connection can be established to enable the vehicles to shareinformation concerning their proximity to one another. This localcommunication will enable one or both vehicles to take correctionactions or alert a driver to chance course or trigger automaticcollision prevention measures (e.g., more aggressive notifications toone or both operators, slow the speed of one or more vehicles, changethe driving direction of one or more vehicles, etc.). Once the closeproximity communication occurs and some corrective action is made, thedata regarding the occurrence and the actions taken can be communicatedto the cloud system for storage. The information can then be viewed by aregistered user having access to an account for the vehicle(s).

FIG. 16B shows one example of a situation 1603 where vehicle 1402 wishesto maneuver automatically without human interaction around a physicalstructure, around an obstacle or to a virtual or physical parkinglocation emitted by a sensor 1408. Vehicle 1402 is in communicationusing its sensor 1404 with the sensor of the second vehicle. Bothvehicles emit their dimensions plus any additional virtual buffer 1602around the physical dimensions of the vehicle. Processing logic on boardeach vehicle use the metrics exchanged between the vehicles to calculateavoidance measures. The buffer 1602 may exist around vehicles,structures, objects or virtual boundaries and may be set statically by ahuman, dynamically in response to collision frequency or remotely by anoperator or manufacturer. In this example, buffers 1602 ensure vehicles,objects and structures to not intersect, thus avoiding collision.

FIG. 16C shows one embodiment 1605 where a portable vehicle charging pador overlay 1514 may be used in conjunction with a virtual parking spotboundary emitted by sensor 1408. In this example, electronics on 1514such as a charging computer 1606 works in conjunction with sensor 1508as well as charge interface and indicator 1608 to provide chargingservices to vehicles utilizing a virtual parking location 1512. Thisexample shows a portable vehicle charging pad or overlay being poweredin a portable fashion by the electrical grid, a generator or solar power1510 in order to pair with 1512 by using 1508 to communicate with 1408as well as registering with cloud processing 120; thus providing acombination of a parking location for a vehicle which also can providevehicle charging facilities.

Once a vehicle has chosen to park or is instructed to park at a parkingspot 1512 being emitted by 1408, the vehicle or vehicle operator orowner may opt to charge the vehicle if it is an electric vehicle (EV). Avehicle's communication sensor can communicate with the sensor on avirtual parking spot or portal vehicle charging pad to indicate to thevehicle operator or owner that charging facilities are available.Furthermore, the owner of an electric vehicle may have chosen to reservenot only the parking space but also charging type in advance. When anelectric vehicle arrives at a parking space where an electric chargingfacility has been reserved, the vehicle will engage the chargingfacility or the charging facility may engage the vehicle to transmit thepurchased charge.

FIG. 17 shows an example system 1700 where a user 180 may interactremotely through the use of cloud processing 120 with a reservationsystem tasked with providing information to users regarding theavailability of networked connected parking spots, whether physical orvirtual as well as reservation and payment facilities 1504. Users mayremotely, though the use of a reservation interface on board a vehicle,remote internet connected device, mobile application etc. to search forand reserve parking and charging faculties in advance. A user may sharethe address, zip code or city they will be traveling to and would liketo locate, reserve and purchase parking and or charging time in advance.

Once user 180 elects a parking space, parking time and or charging timeand space, he or she will be provided instructions for arriving at thedestination parking/charging location. Instructions for auto parking mayalso be sent to the user's vehicle to allow the user to leave theirvehicle at an auto park queue location and walk away while the vehicleis left behind to automatically park without human interaction.Instructions can also be provided to the driver in the form of audioand/or video images (e.g., via a speaker and a display of the vehicle,or linked portable device). The example 1700 shows a listing oftransactional data that may include but is not limited to the shown.

Currently, vehicles maintain very valuable information regarding wherethey are, where they are heading and their destination maintained whichis maintained by GPS and navigation systems on board. The wealth ofinformation collected and maintained by every vehicle is mutuallyexclusive meaning that only each individual vehicle is aware of its ownheading, rate of speed and current location. This information, if crowdsourced and crowd shared/consumed, shared wirelessly vehicle-to-vehicle,can become very powerful in use for accident avoidance, in accordancethe implementations of the present disclosure.

Methods, computer systems, and servers for processing collisionavoidance feedback to vehicles using vehicle-to-vehicle wirelesscommunication, are provided. One method includes detecting proximityseparation between a first vehicle and a second vehicle. At least one ofthe sensors of the first vehicle or the second vehicle determine that aproximity separation is less than a threshold distance. A pairingalgorithm is triggered between electronics of the first and secondvehicle to enable direct communication for data exchange between thefirst and second vehicles. The method includes triggering a warning toone or both of the first and second vehicles if the data exchangedetermines that a probability exists that a heading of the first orsecond vehicles will result in a collision between the first and secondvehicles. The method may initiate corrective action by one or both ofthe first or second vehicles if the data exchange between the first andsecond vehicles increase the probability that the heading will result ina collision between the first and second vehicles.

In one embodiment, by networking vehicles within a certain radius (orsphere, separation, distance, area, geo-location separation, etc.), allor some individually location-aware vehicles, can become aware of othervehicles in their sphere of influence. Some or all of the vehicles cannetwork with other vehicles in their range using wireless communicationsystems, such as but not limited to, Wi-Fi, Wi-Gig LTE, cellular, radio,near field communication or other method.

In some embodiments, vehicle-to-vehicle communication can be implementedusing electronics of the vehicle. In other embodiments, thecommunication can be made using a portable device of the user, which hasa wireless communication mode, and in other embodiments, a vehicle canbe retrofitted to include electronics to enable vehicle-to-vehiclecommunication. This can be done by connecting a circuit or module to aport of the vehicle. The port can be any connector, which allows thecircuit or module to gain access to at least some of the data of thevehicle, such as speed and/or heading, or braking, or stopping, etc. Inother embodiments, the vehicle's native electronics will include thevehicle to vehicle communication electronics to enable the data transferbetween cars to avoid or prevent or reduce collisions.

Each vehicle may maintain a table of all other vehicles in, entering,and or leaving its sphere of influence or some separation. Every vehiclewill maintain and continuously share its own heading, speed andlocation. An algorithm on each vehicle may continuously compare thecurrent vehicle's speed, heading and location with that of all othervehicles in its sphere of influence to determine if a collision mayresult. In one example, some car within a separation can abruptly stop,yet that car is one or more cars ahead of a current car. The current carcannot yet see that an immediate stop will be needed, but because thecar ahead communicates its speed, or movement actions or stops, thatdata can be passed to the user of the car, using a vehicle-to-vehiclewireless communication.

In some implementations, cars can function as moving routers. Forinstance, if a car three car lengths ahead stops, and the car that istwo car lengths head can obtain that information, which is then relayedto the car, which is three cars behind the stopping car. The informationcan therefore be communicated in a relay mode, where one car passesinformation to the next car, and to the next car, and so on, so long asthat information is relevant to the car that is receiving the data. Forinstance, the car receiving the data may be within a separation distanceof the stopping car, and so are the other cars in the relay. The relayof information can be, similar to passing a token from one vehicle toanother, so that the vehicle that has time to act or change its coursecan take advance of the collision avoidance information.

In still other embodiments, the information regarding a car stopped canbe obtained dynamically from the cloud, if the stopping vehicle (whichmay cause an accident), communicated its moving status to the cloud. Theat least one of the other cars in the sphere of influence or separationcan communicate the information to the subject car. Thus, thecommunication can be a hybrid model, where some communication can bevehicle-to-vehicle, and some can be vehicle-to-cloud, and somecommunication can include mode changes (at different times) between andfrom vehicle-to-vehicle and vehicle-to-cloud. Cloud information canprovide data, which can be useful in notifying drivers of possibleproblems, obstacles, or imminent collisions, or conditions that cold ormay cause a collision. Such data can include, weather at thegeo-location of the vehicle and proximate vehicles, reports of actionsor conditions by other users nearby, police reports, social network dataposted by other users, etc. For instance, if the speed of one vehicle isprocessed to be too fast for current weather conditions, this can be aninput to predict or recommend an adjustment in speed, lane change,alternate route, etc., to a vehicle. Once a vehicle has thisinformation, that information can be provided or communicated to otherproximate vehicles, using vehicle-to-vehicle wireless communication.

A vehicle collision is not a single event; it is the intersection thathappens between two vehicles having intended paths, headings, and speedsthat perfectly collide at some point in the future if course correctionis not taken. Thus, an algorithm may be able to predict the probabilityof a future collision where a human may not and alert the driver toalter heading and/or speed. The system will have the ability to enactpassive and active accident avoidance vehicle maneuvers in proactiveaction to an imminent collision.

The system may alert the drivers to change their rate of speed, heading,or location. The system may give each of the two driver's custommessages such as telling both drivers to veer right so they don't steerinto each other. The vehicle may also automatically provide audio and orvisual alerts such as honking the horn or flashing headlights to alertthe other driver. Active accident avoidance may engage if certaincollision is immanent within a certain threshold such as within the next50 ft for example. In this case, both vehicles, being aware of eachother, will engage in an automatic and complementary accident avoidancemaneuver such as slowing down, steering away from impact and or both.The vehicle may engage secondary methods of identifying imminentcollision such as radar, sonar, infrared or other secondary objectidentification method to ensure the predicted collision is not a falsealarm.

The vehicle's cameras can be automatically engaged to take still photosand or video record any incident, whether it results in a successfulavoidance or impact. This footage can be used to alert authorities ofthe severity of the accident and aid insurance companies in identifyingfault. A vehicle will maintain a buffer of events for a given amount oftime before and after a collision event or collision avoidance eventsuch as the location, speed, heading, and avoidance measures to storeand identify the metrics that lead to an incident.

FIG. 18 shows a collection of vehicles all having independent headings,speed and location. Each of the vehicles shown has the ability to becomeaware of all of the other vehicles within a range. Car 1, being oneexample, shows a sample radius of awareness around it. In this example,Car 1 is aware of Car 11, Car 5, Car 9, Car 8, Car 7, Car 3, Car 6, Car2 and Car 4. Car 1 also keeps track of their heading, speed and locationat any given time. Car 1 also knows that Cars 2, 4 and 9 are leaving Car1's sphere of influence. Car 1 also knows that Cars 7, 11, 2 and 6 areentering Car 1's sphere of influence. Just as Car 1 is aware of allother vehicles around it, all other vehicles shown in this diagrambehave in the same manner. For instance, Car 1 is not only keeping trackof all other vehicles in its vicinity, Car 1 is also broadcasting itsspeed, heading and location information so all other Cars in thisdiagram are aware of it as well.

FIG. 19 shows one vehicle, Car 1, communicating wirelessly with othercars around the position of Car1, in one embodiment. In this example,Car 1 is sending its heading, speed and location to all of the othervehicles within communication range and also receiving every othervehicles heading, speed and location within communication range. This isone example, however, all other vehicles within communication range (Car2, 4, 8, 5, 3, 6) are behaving in the same fashion. Car 3 for instancemay not be aware of Car 2 because it is not in communication range.

FIG. 20 shows an instance of an asynchronous network in which allvehicles within a certain communication range can “talk” to each otherusing the same protocol. In this case, the protocol used can be Ethernetthrough wireless mediums such as 802.11a, b, n, ac, ad or any otherwireless communication protocol.

FIG. 21 shows an example system with interfaces, data storagestructures, sensor inputs, algorithms and vehicle control systems usedin collision avoidance on board each vehicle. Each vehicle will have anetwork interface, which communicates with other vehicle's networkinterfaces. Each vehicle may store data coming in from other vehicles incommunication range. This set of data will be kept in a table of allvehicles' metrics including but not limited to speeds, headings,locations, destinations, driving characteristics and acceleration.

Similarly, each vehicle will maintain a table of its own metricsincluding but not limited to speed, heading, location, destination,driving characteristics and acceleration. This data will be passed toother vehicles using the network interface. The vehicle metrics and dataare collected using a variety of sensors including but not limited tooptical sensors, mechanical sensors, and networked sensors among others.Each on board computer on each vehicle will use data coming in fromother vehicles together from data captured by the vehicle itself to feeda collision detection and prediction algorithm.

In one embodiment, each vehicle may have its own privacy settings. Forexample, privacy settings of one car can enable receipt and transfer ofdata regarding speed, heading, location, movements, changes in movement,etc. However, the privacy settings can be configured to be onlytransitory, or have a short lifetime. That is, the data received andshared can expire, so that data cannot be shared outside of the privacysettings. In some embodiments, data is expired can automaticallyscramble or be marked for deletion. For instance, data that is collectedduring a period of time, e.g., during a driving session between 1 pm and2 pm, may only be retained if the data is needed by other vehiclesduring that time frame. That is, if the shared vehicle-to-vehicle datais useful to avoid an accident at a particular period of time, then thatdata may be used, processed, and used to implement vehicle accidentavoidance process. Once that data is not needed for accident avoidance,that data can be erased, deleted, scrambled, or discarded, as dictatedby privacy settings. In other embodiments, that data can be retained,but only based on the settings provided by the user's privacy settings.In some embodiments, data that is shared, but is not traceable to theproviding vehicle, can be retained for any period of time. Such data canlater be used to determine where accidents occurred, may have occurred,times of day when accidences may occur or can occur. This data can beprovided to users by way of websites, services, etc.

In one embodiment, an algorithm will activate a collision managementsystem that interacts with the vehicles control systems including butnot limited to audio alerts, visual alerts, horn, headlamps, steering,braking, video and camera recording, safety restraint systems. Thecollision management system will engage any combination of active and orpassive collision avoidance maneuvers using the vehicle's controlsystems. For instance, if two vehicles are traveling on intended pathsthat will result in a head-on collision, the systems on both vehicleswill calculate if an early warning will suffice. Each of the twovehicles will alert their corresponding driver via audio or visualalert. If the drivers do not correct their intended path and a collisionis still predicted by the algorithm, more aggressive systems will engagesuch as applying braking power or steering the one or both vehicles awayfrom each other.

This is only one example of the various options provided to the userthrough a graphical user interface. As noted above, the graphical userinterface can be integrated with the vehicle, or can be part of a smartdevice that communicates with the vehicle. The smart device thatcommunicates with the vehicle can communicate using wireless technologyso that metrics associate with the vehicle and location of the vehiclecan be obtained and then communicated to the cloud processing toexchange information.

FIG. 22 illustrates one example of metrics data that can be obtained bya transportation vehicle (TV), and communication to and from othernetworked TVs, in accordance with one embodiment of the presentinvention. In this example, information can be obtained from aparticular vehicle, such as service and repair history, whether user iswilling to sell or exchange the vehicle, the replacement cost of thevehicle versus repairing the vehicle, the replacement part cost of avehicle, parts to replace for vehicle (as known from historical data ofthe same vehicle, or based on a current malfunction), the fuel rates,fuel locations for charge, route generators, modification suggestionsfor driving to increase performance, accident avoidance data, comparablevehicle current market price, recall information for the currentvehicle, etc.

This information can be obtained from the vehicle or from the users ofthe vehicle. This information can also be obtained by the cloudprocessing which communicate with other systems connected to theInternet. Other systems can be data stores for information concerningthe same vehicle, historical data concerning potential breakdown of thevehicle, price estimates of the vehicle, marketplace data concerningexchange the vehicle, etc. This information can be provided at thevehicle to the user through a computer user interface. On demand, theuser can determine whether it's worthwhile to exchange the vehicle foranother vehicle, and the potential of the current vehicle to break down.

Furthermore, the user may decide that it's time to exchange the vehiclefor new vehicle, and market rates for the current vehicle based onactual vehicle data of the user's vehicle, can be used to identify itscurrent market price. The current market price for replacement vehiclecan also be obtained dynamically, and comparable data can be presentedto the user in the user interface. Accordingly, the user would not haveto input information concerning its vehicle into the user interfacesimply to figure out what the market price is. The data concerning thevehicle is inherently collected and stored in the vehicle memory basedon vehicle use, age, accidents, condition, etc. Additionally,information concerning available vehicles near the user which may be forsale can also be attained dynamically and in real time.

For example if the user wishes to replace the vehicle, the user cansimply click a button, select an icon, touch a screen, speak a command,gesture an input, etc., to figure out what his vehicle value is, thecost of a replacement vehicle, and the total cost after exchange. Thisinformation can be useful to the user in deciding whether or not totrade in the vehicle or remain with the current vehicle and makeinvestments in repairs. As shown, the data exchange between vehicles andthe vehicles and the cloud processing can be extensive, but suchinformation can be made available to drivers of those vehicles to makeinformed decisions.

Cloud processing 120 technology is also provided, which providesprocessing resources to connected vehicles through a distributednetwork. In one embodiment, for electric vehicles, the cloud processingcan communicate with various charging stations using Internetconnections, where charge station metrics can be uploaded to the cloudprocessing system. The charge Station metrics can include availabilityof charge pumps, charge handles, charge plugs, charge mats (for wirelesschagrining), volt bars, or other charge providing facilities.

Examples of such metrics can include the number of charge pumpsavailable at particular period of time, historical availability times ofthe charge pumps, typical charge time estimates at particular chargingstations, prices associated with the charge at the particular chargingstations, feedback from customers through social networks, concerningthe charging stations, and the like. The cloud processing can thenprocess the charge station status, traffic information associated withlocations around or between charging stations and a user's currentlocation, and provide specific suggested routes displayed on the user'sdevice 103 or sent to user 180's vehicle(s) or portable programmablevehicle profile(s). The route generator can provide guided routes to thevarious charging stations (e.g., charge locations), based on the user's180 immediate needs, desire for discounts, sponsored rewards, or theamount of time it will take to obtain access to a charge pump at aparticular point in time. Broadly speaking, a discount is a reward and areward is a discount, and a sponsored reward is a discount that is atleast partially paid by another party for a benefit of the recipient ofthe reward.

The driver location processor can communicate the information concerningdrivers to the cloud processing logic 120, so as to provide the mosteffective information concerning charge availability to the variousdrivers. For example, users in their particular vehicles may have aconnected display or a portable device having access to the Internet.Based on the user's location and charging needs, (and optionally thedestination) the user can be provided with route options (e.g., one ormore optional paths). The route options can be, for example, the fastestand most available charge Station (or charge providing devices) to theusers current location, the cheapest charge available at a particularpoint in time, or information regarding charge prices for a particularfuture point in time.

Once the user selects a route option, the route generator can provideinformation concerning the charging station, and can also prepay or booka charging station slot. A charging station slot can include, forexample a parking spot in front of a charging station. The chargingstation slot can be reserved if the user decides to prepay for thecharging station, as a convenience. For example, if charging slots at aparticular charge Station appear to be heavily used, a user canpre-reserve a charging slot ahead of time, so that when the user arrivesat the charging station, the charging slot will be immediatelyavailable. This could be considered a convenience fee associated withpre-reserving of a charging slot, along a particular route. In anotherembodiment, the charging station can provide incentives to users to cometo the particular charging station.

For example, if the user prepays for charge at a particular chargingstation, the charging station can provide a discount on the chargeprovided. For example, if the charging station wishes to fill aplurality a charging slots during a particular slow time, the chargingstation can communicate with the cloud processing and publishavailability of its charging stations per particular period of time. Adatabase associated with cloud processing will hold this information soit can be dynamically updated and accessed in real-time by users to filltheir charging needs of their electric vehicles.

During that particular period of time, the charging station can offerdiscounts or rewards to users so that drivers can decide to visit thecharging station instead of another charging station. Still further,charging stations can offer discounts for users to use the particularcharging station, and the discounts can be offered by more than oneparty or entity. For instance, if the charging stations are located neara particular business, that particular business can sponsor discounts orrewards at the charging station to drive traffic to or near thatparticular business. When users are charging their vehicles at theparticular station near the particular business, users can spend theirtime at the particular business while their vehicle is being charged.

Again, the information displayed to the user can be displayed in thevehicle's display screen or can be displayed on the users display device(e.g. smart phone, computer, tablet, etc.).

In one embodiment, a method for customizing advertisements at a locationincludes: (a) detecting presence of a vehicle at the location, thevehicle being registered to a user account that manages remote access tothe vehicle over cloud processing logic on the Internet; (b) determiningpreferences for a user account; and (c) modifying display advertisementsto show ad content that best matches ad content relevant to the useraccount, wherein the display advertisements include display screensviewable to occupants of the vehicle when the vehicle is detected to bepresent at the location.

It will be obvious, however, to one skilled in the art, that the presentinvention may be practiced without some or all of these specificdetails. In other instances, well known process operations have not beendescribed in detail in order not to unnecessarily obscure the presentinvention.

Embodiments of the present invention may be practiced with variouscomputer system configurations including hand-held devices,microprocessor systems, microprocessor-based or programmable consumerelectronics, minicomputers, mainframe computers and the like. Theinvention can also be practiced in distributed computing environmentswhere tasks are performed by remote processing devices that are linkedthrough a wire-based or wireless network.

With the above embodiments in mind, it should be understood that theinvention could employ various computer-implemented operations involvingdata stored in computer systems. These operations are those requiringphysical manipulation of physical quantities. Usually, though notnecessarily, these quantities take the form of electrical or magneticsignals capable of being stored, transferred, combined, compared andotherwise manipulated.

Any of the operations described herein that form part of the inventionare useful machine operations. The invention also relates to a device oran apparatus for performing these operations. The apparatus can bespecially constructed for the required purpose, or the apparatus can bea general-purpose computer selectively activated or configured by acomputer program stored in the computer. In particular, variousgeneral-purpose machines can be used with computer programs written inaccordance with the teachings herein, or it may be more convenient toconstruct a more specialized apparatus to perform the requiredoperations.

The invention can also be embodied as computer readable code on acomputer readable medium. The computer readable medium is any datastorage device that can store data, which can thereafter be read by acomputer system. The computer readable medium can also be distributedover a network-coupled computer system so that the computer readablecode is stored and executed in a distributed fashion.

Although the foregoing invention has been described in some detail forpurposes of clarity of understanding, it will be apparent that certainchanges and modifications can be practiced within the scope of theappended claims. Accordingly, the present embodiments are to beconsidered as illustrative and not restrictive, and the invention is notto be limited to the details given herein, but may be modified withinthe scope and equivalents of the description.

What is claimed is:
 1. A method for navigating a vehicle automaticallyfrom a current location to a destination location without a humanoperator, the method comprising: identifying a vehicle location usingglobal positioning system (GPS) data regarding the vehicle; identifyingthat the vehicle location is near or at a parking location; usingmapping data defined for the parking location, the mapping data at leastin part used to find a path at the parking location to avoid a collisionof the vehicle with at least one physical structure when the vehicle isautomatically moved at the parking location, wherein the mapping data isprocessed by electronics of the vehicle so that when the vehicle isautomatically moved collision with the at least one physical structureis avoided; instructing the electronics of the vehicle to proceed withcontrolling the vehicle to automatically move from the current locationto the destination location at the parking location, the electronics useas input at least part of the mapping data and sensor data collectedfrom around the vehicle by at least two vehicle sensors, the path isconfigured to be updatable dynamically based on changes in thedestination location or changes along the path, the destination locationbeing a parking spot for the vehicle at the parking location.
 2. Themethod of claim 1, wherein the parking location includes a plurality ofsensors, and data of at least one of said sensors is communicated to theelectronics of the vehicle.
 3. The method of claim 2, wherein sensors ofthe vehicle and sensors of the parking location are used to avoidcollision with objects in the parking location.
 4. The method of claim2, wherein the sensors of the parking location include sensors of one ormore vehicles located in the parking location.
 5. The method of claim 1,wherein the parking location is one of a parking garage, a parking lot,a private property area, a garage and drive-way, a private residence, apublic location, or a combination of private and public spaces.
 6. Themethod of claim 6, wherein instructing the electronics of the vehicle toproceed with controlling the vehicle to automatically is initiated via aremote computing device, and the remote computing device is a computingdevice that is either portable or not portable and the remote computingdevice has access to the Internet to communicate with a server and theelectronics of the vehicle, the electronics of the vehicle enablingwireless communication via one or more of a peer-to-peer communication,or Wi-Fi communication, or a near field communication (NFC), or aBluetooth communication.